Monitoring of components of industrial power systems, such as electrical plants and substations, is important for continuous operation of the industrial power systems. The components, such as transformers, motors, feeders, generators, circuit breakers, and so forth, are expected to run constantly for long periods of time. The monitoring may allow detecting events related to operation of the components and predict issues associated with health or condition of the components. When an issue is detected, a diagnosis and a root cause can be reported to a user so the user can take measures minimizing or resolving the issue. Monitoring of important components of industrial power systems may provide insight into components' health in order to improve reliability and efficiency of the components, increase production capacity of the components, and avoid unexpected costs in their maintenance.
Conventional solutions for monitoring and diagnostics of electrical power system components are very complex and are typically designed for specific components so that they cannot be easily adjusted to components of different types and sizes. For example, conventional solutions cannot be adjusted for use as part of intelligent electronic devices (IEDs), such as digital protection relays. Furthermore, costs associated with the conventional monitoring solutions do not typically correspond to costs of components being monitored. Additionally, conventional monitoring and diagnostics solutions typically cannot provide reliable predictions with regard to health of components as they are using limited information and data available to IEDs. Moreover, existing solutions for monitoring and diagnostics can be prone to measurement and accuracy related errors. Monitoring and diagnostics solutions used for providing analytics concerning a health state of components of industrial power systems are typically based on limited data.